Investment Fund Management [3]
论文作者:www.51lunwen.org论文属性:作业 Assignment登出时间:2014-06-09编辑:lzm点击率:4932
论文字数:2041论文编号:org201406091511134402语种:英语 English地区:中国价格:免费论文
关键词:Investment Fund Managementstatistical analysiscorrelation coefficient统计分析技术分析处理
摘要:If the correlation exists between the above two factors then it could mean either one of them influences the other or both of them influence each other consistently or intermittently or both of them are influenced by some other third factor or the correlation could be out of pure chance.
he actual means and not from the assumed means. Correlationcoefficient can also be obtained directly without taking the deviations of theitems either from actual means or assumed means by the formula r = (Nixie - SxSy) / {[NSx2 -(Sx)1/2][NSy2- (Sy)1/2]}1/2where x and y are the values of the variables X and Y respectively and not thedeviations from the means as in the earlier formulas. When the deviations aretaken from assumed means(for example, if the values of X and Y are integral butthe means involve fractions the to make calculations simple we take deviationsfrom some integers near to the actual means which are called assumed means) theformula is identical as the one given immediately before with the onlydifference that the actual values of x and y are replaced by the deviationsfrom the assumed means. The Pearsonaion correlation coefficient is based on theassumptions that i) there is a linear relationship between the variables, ii)the two variables form a normal distribution and iii) there is a cause andeffect relationship between the variables. The chief limitations of this methodare i) linear relationship between the variables is assumed ii) the coefficientis prone to misinterpretation iii) the coefficient is unduly affected byextreme items iv) comparatively more time consuming.
Rank correlation coefficient: - This was developed by the British psychologist, Charles EdwardSpearman and hence named after him. This method does not assume any thing aboutthe parameters of the population or the shape of the distribution. This methodis especially useful when quantitative measures of certain factors cannot befixed but the members of the group can be ranked. The Spearman's rankcorrelation coefficient is defined as rs = 1 - (6SD2) /N (N2 -1) where D de
notes the difference of ranks between paireditems. The advantages of this method are i) simpler to understand and easier toapply and if all items are different the coefficient is same as Pearsonian's. ii)advantageous for the data of qualitative nature. For example, surgeons in twocountries can be ranked in order of professionalism and the degree ofcorrelation can be established by applying this method. iii) this is the onlymethod that can be used when the actual data is not given but only the ranksare given iv) even where actual data are given this method can be applied. Itslimitations are that it cannot be used for finding out correlation in groupedfrequency distribution and it cannot be used if the number of items exceed 30
Concurrent deviation method :- This is the simplest of all methods. The formula is rc =+[+(2C -N)/N]1/2 where C stands for the number of concurrent deviations and N = number of pairs of observations less 1. The method is simplest of all and may be used to form a quick idea about the degreeof relationship before making use of more complicated methods. It's limitations are that it does not differentiate between small and big changes. For example,if X changes from 100 to 101 the sign will be plus and if Y changes from 100 to160 the sign will be plus. The results obtained from this method are only arough indicator of the presence or absence of correlation.
Interpretation of correlation coefficient :- the correlation coefficient is often likely to be misinterpreted. A large amount of experience is required to interpret it properly. The general rules of interpreting are :
r = +1 means there is perfect posi
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